Closely-coupled processors or hardware resources will become widely available within the near future. Examples of such closely-coupled processors (or hardware resources) may include additional processors, threads in a particular processor, additional cores in a central processing unit, additional processors mounted on the same substrate or board, and/or such devices provided within computers connected by a network fabric into a cluster, a grid, or a collection of resources.
Certain computations (e.g., parallel processing or parallel programming) may benefit from the availability of such hardware resources. For example, a complex simulation may run faster if the simulation is divided into portions and the portions are simultaneously run on a number of processing devices in a parallel fashion. Parallel computing arrangements may include a controller that determines how an application should be divided and what application portions go to which parallel processors. For example, a host computer that is running a simulation may act as the controller for a number of parallel processors.
Parallel processors may receive instructions and/or data from the controller and may return a result to the controller. Conventional parallel programming language constructs do not nest or, if they can nest, provide an outermost construct with complete control of the allocation of hardware resources while executing inner constructs serially. Such an “outermost” strategy may degrade the performance of library routines executing such parallel constructs, without yielding corresponding benefits.
Conventional parallel programming environments either provide a very flexible framework or a restricted framework. The flexible framework allows a user to perform a variety of parallel programming actions, but such flexibility increases the probability of committing errors. The restricted framework does not allow the user to perform sufficient parallel programming actions. Examples of conventional attempts at parallel programming may include a distributed operating system (OS), an open MOSIX (a management system for Linux clusters and organizational grids), and/or Java™ threads. However, a distributed OS fails to provide dynamic, cross-platform, and interactive parallel programming. An open MOSIX may enable a user to migrate execution threads across multiple devices, but cannot appropriately deal with mode changes caused by parallel programming. Java™ threads are similar to an open MOSIX, but do not provide a parallel programming environment. Rather, Java™ threads represent just a building block towards a parallel programming environment.